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Record W6884608379 · doi:10.1139/cjps2013-302

The effect of simulated winter warming spells on Canada fleabane [Conyza canadensis (L.) Cronq. var. canadensis] seeds and plants

2014· article· en· W6884608379 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOverwinteringDormancySpring (device)Global warmingSeedling

Abstract

fetched live from OpenAlex

Experiments were establish at three sites in southern Ontario, Canada in 2009 and 2010 to determine the possible effect of winter warming spells applied in either January, February or March on seed, seedlings, or rosettes of Canada fleabane including effects on winter survival, fecundity, above-ground biomass, and flowering timing. Warming spells reduced survival of fall-established rosettes and fall established seedlings. Warming spells occurring late in winter (March) had a greater effect where March warming spells reduced the survival of rosettes and seedlings on average by 53% and 80%, respectively. In addition, overwintering Canada fleabane plants (rosettes or seedlings) exposed to warming spells flowered earlier (between 29 and71 days earlier). This study also confirms that Canada fleabane seed has little or no dormancy and that the great majority of seed recruits (either in fall or spring) within a given season (between 84% and 93%). We also determined that timing of seed shed in the fall significantly affects the proportion of seedlings emerging either in the spring or fall with late shed favoring seed overwintering and spring seedling emergence. The results of this study suggest that winter warming spells, especially later in the winter (into early spring), may limit the success of Canada fleabane and in particular its success as a winter annual.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.108
GPT teacher head0.208
Teacher spread0.100 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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